1. Field of the Invention
The present disclosure relates to computed tomography (“CT”) systems generally, and more particularly, to a method for applying iterated coordinate descent (“ICD”) to handle material decomposition (“MD”) for energy discriminating computed tomography (“EDCT”) acquisitions.
2. Description of Related Art
CT systems are now becoming available that collect data using multiple spectra (i.e., multiple kVPs or multiple filtrations) or that collect data using energy discriminating detectors (e.g., layered energy integrating detectors or photon counting detectors). In such configurations, the collected data contains information about the material composition of the scanned object. This information is typically expressed as the atomic number or as the photoelectric and Compton components of the scanned object.
Known reconstruction algorithms take these indirect line-integral measurements and create volumetric representations of the object from which detection or diagnosis can take place. Additionally, it is known that iterative and statistical reconstruction techniques outperform non-iterative techniques in creating the volumetric representations. In particular, for the same resolution iterative and/or statistical methods can show a significant reduction in image noise. We refer to reconstruction algorithms (iterative, statistical or otherwise) that use a polychromatic spectrum without energy discrimination capability to be “polychromatic” algorithms. This includes, for example, the state of the art in iterative and non-iterative reconstruction.
For example, traditional iterated coordinate descent (“ICD”), used in either 2D or 3D variants to reconstruct X-ray attenuation for a pixel, involves:
1. forming an initial image;
2. performing a sequence of iterations;
3. for each iteration, visiting each of the pixels in the image in turn; and
4. for each pixel visited with an iteration, replacing the pixel's scalar value with a new scalar value, which is computed by optimizing a cost function on the image as a whole, where all other pixels in the image are fixed at an estimated scalar value.
Consequently, only a single component needs be determined, and that is the new scalar value for each pixel visited with an iteration.
What is needed is a novel extension of polychromatic iterative and/or statistical reconstruction methods to handle the multiple energy data collected by an energy discriminating computed tomography (“EDCT”) system.